Noise-Invariant Agentic Human-Robot Interaction GenAI System Using a Dual-Encoder Contrastive ASR Architecture and VLMs for Robot Control and Navigation in Acoustically Challenging Jobsites
This paper proposes an HRI agentic artificial intelligence system—integrating a construction domain-specific, noise-robust automatic speech recognition (ASR) agent and a vision-language model (VLM)-based robotic control agent—to reliably transcribe speech in noisy environments and parse instructions for robot navigation in acoustically challenging construction jobsites.